cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)
lin = Pipeline([
("scaler", StandardScaler()),
("lr", LogisticRegression(max_iter=1000))
])
stack = StackingClassifier(estimators=[("lin", lin)],
final_estimator=LGBMClassifier(),
stack_method="predict_proba", passthrough=True, cv=cv
)
stack.fit(X_train, y_train)
y_pred = stack.predict(X_test)